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  • Segmentation of Pulmonary Nodules in Computed Tomography Using a Regression Neural Network Approach and its Application to the Lung Image Database Consortium and Image Database Resource Initiative Dataset (Pulmonary-Nodules-Segmentation)

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Localtab Group


Localtab
activetrue
titleData Access

Data Access

Click the Download button to save a ".tcia" manifest file to your computer, which you must open with the NBIA Data Retriever

Data TypeDownload all or Query/Filter

Images containing the 66 testing nodules that are delineated by all four board certified radiologists (DICOM) 

Images containing the 77 LIDC testing nodules that are segmented by three or more radiologists (DICOM)

Please contact help@cancerimagingarchive.net  with any questions regarding usage.


Localtab
titleCitations & Data Usage Policy

Citations & Data Usage Policy 

Public collection license

Info
titleData Citation

Messay T, Hardie RC,  Tuinstra TR. (2014). Segmentation of Pulmonary Nodules in Computed Tomography Using a Regression Neural Network Approach and its Application to the Lung Image Database Consortium and Image Database Resource Initiative Dataset. The Cancer Imaging Archive. https://doi.org/10.7937/K9/TCIA.2014.V7CVH1JO



Info
titlePublication Citation

Messay T, Hardie RC,  Tuinstra TR. (2015). Segmentation of pulmonary nodules in computed tomography using a regression neural network approach and its application to the Lung Image Database Consortium and Image Database Resource Initiative dataset. Medical Image Analysis. Elsevier BV. https://doi.org/10.1016/j.media.2015.02.002



Info
titleTCIA Citation

Clark, K., Vendt, B., Smith, K., Freymann, J., Kirby, J., Koppel, P., Moore, S., Phillips, S., Maffitt, D., Pringle, M., Tarbox, L., & Prior, F.  The (2013). The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository, . In Journal of Digital Imaging , Volume (Vol. 26, Number Issue 6, December, 2013, pp 1045-1057. (paper)

In addition to the dataset citation above, please be sure to cite the following if you utilize these data in your research:

Info
titlePublication Citation

Messay T, Hardie RC,  Tuinstra TR. (2015). Segmentation of pulmonary nodules in computed tomography using a regression neural network approach and its application to the Lung Image Database Consortium and Image Database Resource Initiative dataset. Medical Image Analysis. Elsevier BV1045–1057). Springer Science and Business Media LLC. https://doi.org/10.1016/j.media.2015.02.0021007/s10278-013-9622-7 PMCID: PMC3824915

Other Publications Using This Data

TCIA maintains a list of publications that leverage TCIA data. If you have a manuscript you'd like to add please contact the TCIA Helpdesk.

  • Gomes, J. H. O. (2017). Pulmonary nodule segmentation in computed tomography with deep learning. (M.S. Thesis). Instituto Universitário de Lisboa, Retrieved from http://hdl.handle.net/10071/15479


Localtab
titleVersions

Version 1 (Current): 2015/02/24


Data TypeDownload all or Query/Filter

Images containing the 66 testing nodules that are delineated by all four board certified radiologists (DICOM) 

Images containing the 77 LIDC testing nodules that are segmented by three or more radiologists (DICOM)



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